Study of Aluminum Degasification with Impeller-Injector Assisted by Physical Modeling

2012 ◽  
Vol 1485 ◽  
pp. 41-46
Author(s):  
M. Hernández-Hernández ◽  
E. A. Ramos-Gómez ◽  
M. A. Ramírez-Argáez
Keyword(s):  
Physical Model ◽  
Gas Flow ◽  
Liquid Aluminum ◽  
Gas Injection ◽  
The Novel ◽  
Rotating Speed ◽  
Novel Method ◽  
Purge Gas ◽  
Efficiency And Productivity ◽  
Kinetics Of

ABSTRACTA full-scale water physical model of a degassing unit is built and used to evaluate the performance of several impeller designs. Four impeller designs are tested: a) one smooth not commercial impeller for reference purposes, b) a commercial design by FOSECO®, called standard impeller in this work, c) a commercial design by FOSECO® with notches, and d) a new design proposed in this work. Since the physical model is easy and safe to operate, a full experimental design is performed to evaluate the effect of the most important process variables, such as impeller rotating speed, gas flow rate, impeller design and the point of gas injection (a conventional gas injection through the shaft and a novel method of injecting gas through the bottom of the ladle) on the kinetics of oxygen desorption of water which is similar to dehydrogenation of liquid aluminum. The new design of impeller proposed in this work shows the best performance in degassing of all impellers tested in this study. It is found that the rotor speed and its design are the most significant variables affecting degassing kinetics, and therefore the analysis of the existing commercial impeller designs may be useful to optimize the fluid dynamics of the process, which in turn would increase efficiency and productivity of the process. Finally, the novel gas injection method through the bottom, proposed by our own group, presents slightly faster degassing kinetics than the conventional injection of purge gas in the conventional way through the impeller.

Mathematical modeling of aluminum degassing by the impeller injector technique validated by a physical modeling

2014 ◽  
Vol 1611 ◽  
pp. 49-54 ◽  
Author(s):  
M. Hernández-Hernández ◽  
W. F. Cruz-Mendez ◽  
C. Gonzalez-Rivera ◽  
M. A. Ramírez-Argáez
Keyword(s):  
Mathematical Model ◽  
Physical Model ◽  
Gas Flow ◽  
Process Analysis ◽  
Liquid Aluminum ◽  
Bubble Diameter ◽  
Operating Parameter ◽  
Gas Flow Rate ◽  
The Mathematical Model ◽  
Kinetics Of

ABSTRACTA mathematical model is developed to describe deoxidation of water in a physical model of a batch aluminum degassing reactor equipped with the rotor-injector technique, assuming that deoxidation kinetics of water is similar to dehydrogenization of liquid aluminum. Degassing kinetics is described by using mass transport and mass balance principles by assuming that degassing kinetics can be characterized by a mass transfer coefficient, which depends on the process variables. The transport coefficient and the average bubble diameter are estimated with correlations reported in the literature for similar gas-injection systems. The water physical model helped to validate the mathematical model and to perform a process analysis by varying: 1) Gas flow rate (20 and 40 l/min); and 2) Impeller’s angular velocity (290 and 573 rpm). Results from the model agree well with measurements of deoxidation kinetics at low impeller rotating speeds. At high rotating speeds the model is still valid but less reliable because it does not take into account the formation of the vortex at the free surface. Nevertheless, the model provides predictions of the influence of every operating parameter and it can be used as a good approximation for real systems.

scholarly journals The Influence of Varying Fluorination Patterns on the Thermodynamics and Kinetics of Benzenesulfonamide Binding to Human Carbonic Anhydrase II

Biomolecules ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 509 ◽  
Author(s):  
Steffen Glöckner ◽  
Khang Ngo ◽  
Björn Wagner ◽  
Andreas Heine ◽  
Gerhard Klebe
Keyword(s):  
Carbonic Anhydrase ◽  
Carbonic Anhydrase Ii ◽  
The Novel ◽  
Binding Modes ◽  
X Ray ◽  
Structure Activity ◽  
Small Set ◽  
Novel Method ◽  
Human Carbonic Anhydrase ◽  
Kinetics Of

The fluorination of lead-like compounds is a common tool in medicinal chemistry to alter molecular properties in various ways and with different goals. We herein present a detailed study of the binding of fluorinated benzenesulfonamides to human Carbonic Anhydrase II by complementing macromolecular X-ray crystallographic observations with thermodynamic and kinetic data collected with the novel method of kinITC. Our findings comprise so far unknown alternative binding modes in the crystalline state for some of the investigated compounds as well as complex thermodynamic and kinetic structure-activity relationships. They suggest that fluorination of the benzenesulfonamide core is especially advantageous in one position with respect to the kinetic signatures of binding and that a higher degree of fluorination does not necessarily provide for a higher affinity or more favorable kinetic binding profiles. Lastly, we propose a relationship between the kinetics of binding and ligand acidity based on a small set of compounds with similar substitution patterns.

scholarly journals Numerical Modeling of Equal and Differentiated Gas Injection in Ladles: Effect on Mixing Time and Slag Eye

Processes ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 917
Author(s):  
Luis E. Jardón-Pérez ◽  
Carlos González-Rivera ◽  
Marco A. Ramirez-Argaez ◽  
Abhishek Dutta
Keyword(s):  
Numerical Modeling ◽  
Numerical Model ◽  
Physical Model ◽  
Flow Rate ◽  
Gas Flow ◽  
Mixing Time ◽  
Gas Injection ◽  
Steel Slag ◽  
Gas Flow Rate ◽  
Slag Thickness

Ladle refining plays a crucial role in the steelmaking process, in which a gas stream is bubbled through molten steel to improve the rate of removal of impurities and enhance the transport phenomena that occur in a metallurgical reactor. In this study, the effect of dual gas injection using equal (50%:50%) and differentiated (75%:25%) flows was studied through numerical modeling, using computational fluid dynamics (CFD). The effect of gas flow rate and slag thickness on mixing time and slag eye area were studied numerically and compared with the physical model. The numerical model agrees with the physical model, showing that for optimal performance the ladle must be operated using differentiated flows. Although the numerical model can predict well the hydrodynamic behavior (velocity and turbulent kinetic energy) of the ladle, there is a deviation from the experimental mixing time when using both equal and differentiated gas injection at a high gas flow rate and a high slag thickness. This is probably due to the insufficient capture of the velocity field near the water–oil (steel–slag) interface and slag emulsification by the numerical model, as well as the complicated nature of correctly simulating the interaction between both gas plumes.

Effect of Hole Distance and Hole Number on Bubble Behavior during Gas Injection with Multi-Hole Orifices

2011 ◽  
Vol 295-297 ◽  
pp. 1113-1119 ◽  
Author(s):  
Fang Jiang ◽  
Guo Guang Cheng
Keyword(s):  
Physical Model ◽  
Flow Rate ◽  
Gas Flow ◽  
Gas Injection ◽  
Critical Value ◽  
Refining Process ◽  
Hole Diameter ◽  
Gas Flow Rate ◽  
Bubble Behavior ◽  
Hole Number

Physical model experiments have been performed to clarify the effect of hole distance and hole number of multi-hole orifices on bubble behavior during metal refining process. It is found kA/V firstly decreases and then increases with the hole distance increasing. However, kA/V shows little further increase when hole distance exceeds a critical value. There exists an optimal hole distance for the multi-hole orifice, which is dependent on the gas flow rate, the hole diameter and the hole number in the multi-hole orifice. kA/V firstly increases with the hole number increasing, and then remains unchanged when hole number exceeds a critical value. There also exists an optimal hole number for the multi-hole orifice, which is closely related to the gas flow rate.

A novel method for the determination of linting propensity of paper

TAPPI Journal ◽  
2012 ◽  
Vol 11 (10) ◽  
pp. 9-17
Author(s):  
ALESSANDRA GERLI ◽  
LEENDERT C. EIGENBROOD
Keyword(s):  
Ash Content ◽  
The Novel ◽  
Offset Printing ◽  
Excellent Correlation ◽  
End Conditions ◽  
Bottom Side ◽  
Novel Method ◽  
Total Fraction

A novel method was developed for the determination of linting propensity of paper based on printing with an IGT printability tester and image analysis of the printed strips. On average, the total fraction of the surface removed as lint during printing is 0.01%-0.1%. This value is lower than those reported in most laboratory printing tests, and more representative of commercial offset printing applications. Newsprint paper produced on a roll/blade former machine was evaluated for linting propensity using the novel method and also printed on a commercial coldset offset press. Laboratory and commercial printing results matched well, showing that linting was higher for the bottom side of paper than for the top side, and that linting could be reduced on both sides by application of a dry-strength additive. In a second case study, varying wet-end conditions were used on a hybrid former machine to produce four paper reels, with the goal of matching the low linting propensity of the paper produced on a machine with gap former configuration. We found that the retention program, by improving fiber fines retention, substantially reduced the linting propensity of the paper produced on the hybrid former machine. The papers were also printed on a commercial coldset offset press. An excellent correlation was found between the total lint area removed from the bottom side of the paper samples during laboratory printing and lint collected on halftone areas of the first upper printing unit after 45000 copies. Finally, the method was applied to determine the linting propensity of highly filled supercalendered paper produced on a hybrid former machine. In this case, the linting propensity of the bottom side of paper correlated with its ash content.

scholarly journals REMAXINT: a two-mode clustering-based method for statistical inference on two-way interaction

2021 ◽  
Author(s):  
Zaheer Ahmed ◽  
Alberto Cassese ◽  
Gerard van Breukelen ◽  
Jan Schepers
Keyword(s):  
Null Hypothesis ◽  
Type I Error ◽  
Type I ◽  
The Novel ◽  
Simulation Studies ◽  
Test Statistic ◽  
Clustering Model ◽  
Novel Method ◽  
Main Effects ◽  
Empirical Case Studies

AbstractWe present a novel method, REMAXINT, that captures the gist of two-way interaction in row by column (i.e., two-mode) data, with one observation per cell. REMAXINT is a probabilistic two-mode clustering model that yields two-mode partitions with maximal interaction between row and column clusters. For estimation of the parameters of REMAXINT, we maximize a conditional classification likelihood in which the random row (or column) main effects are conditioned out. For testing the null hypothesis of no interaction between row and column clusters, we propose a $$max-F$$ m a x - F test statistic and discuss its properties. We develop a Monte Carlo approach to obtain its sampling distribution under the null hypothesis. We evaluate the performance of the method through simulation studies. Specifically, for selected values of data size and (true) numbers of clusters, we obtain critical values of the $$max-F$$ m a x - F statistic, determine empirical Type I error rate of the proposed inferential procedure and study its power to reject the null hypothesis. Next, we show that the novel method is useful in a variety of applications by presenting two empirical case studies and end with some concluding remarks.

scholarly journals Interrogating the Egypto-Sudanic Arabic Connection

Languages ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 123
Author(s):  
Thomas A. Leddy-Cecere
Keyword(s):  
The Novel ◽  
Present Contribution ◽  
Phonological Processes ◽  
Verbal Inflection ◽  
Segmental Phonology ◽  
Language Data ◽  
History Of ◽  
Novel Method ◽  
Dialect Classification ◽  
Arabic Speaking

The Arabic dialectology literature repeatedly asserts the existence of a macro-level classificatory relationship binding the Arabic speech varieties of the combined Egypto-Sudanic area. This proposal, though oft-encountered, has not previously been formulated in reference to extensive linguistic criteria, but is instead framed primarily on the nonlinguistic premise of historical demographic and genealogical relationships joining the Arabic-speaking communities of the region. The present contribution provides a linguistically based evaluation of this proposed dialectal grouping, to assess whether the postulated dialectal unity is meaningfully borne out by available language data. Isoglosses from the domains of segmental phonology, phonological processes, pronominal morphology, verbal inflection, and syntax are analyzed across six dialects representing Arabic speech in the region. These are shown to offer minimal support for a unified Egypto-Sudanic dialect classification, but instead to indicate a significant north–south differentiation within the sample—a finding further qualified via application of the novel method of Historical Glottometry developed by François and Kalyan. The investigation concludes with reflection on the implications of these results on the understandings of the correspondence between linguistic and human genealogical relationships in the history of Arabic and in dialectological practice more broadly.

scholarly journals Suspended Sediment Modeling Using a Heuristic Regression Method Hybridized with Kmeans Clustering

2021 ◽  
Vol 13 (9) ◽  
pp. 4648
Author(s):  
Rana Muhammad Adnan ◽  
Kulwinder Singh Parmar ◽  
Salim Heddam ◽  
Shamsuddin Shahid ◽  
Ozgur Kisi
Keyword(s):  
Clustering Algorithm ◽  
Suspended Sediments ◽  
Ecological Impacts ◽  
Accurate Estimation ◽  
Data Sets ◽  
The Novel ◽  
Neuro Fuzzy ◽  
Adaptive Regression ◽  
Novel Method ◽  
Model Training

The accurate estimation of suspended sediments (SSs) carries significance in determining the volume of dam storage, river carrying capacity, pollution susceptibility, soil erosion potential, aquatic ecological impacts, and the design and operation of hydraulic structures. The presented study proposes a new method for accurately estimating daily SSs using antecedent discharge and sediment information. The novel method is developed by hybridizing the multivariate adaptive regression spline (MARS) and the Kmeans clustering algorithm (MARS–KM). The proposed method’s efficacy is established by comparing its performance with the adaptive neuro-fuzzy system (ANFIS), MARS, and M5 tree (M5Tree) models in predicting SSs at two stations situated on the Yangtze River of China, according to the three assessment measurements, RMSE, MAE, and NSE. Two modeling scenarios are employed; data are divided into 50–50% for model training and testing in the first scenario, and the training and test data sets are swapped in the second scenario. In Guangyuan Station, the MARS–KM showed a performance improvement compared to ANFIS, MARS, and M5Tree methods in term of RMSE by 39%, 30%, and 18% in the first scenario and by 24%, 22%, and 8% in the second scenario, respectively, while the improvement in RMSE of ANFIS, MARS, and M5Tree was 34%, 26%, and 27% in the first scenario and 7%, 16%, and 6% in the second scenario, respectively, at Beibei Station. Additionally, the MARS–KM models provided much more satisfactory estimates using only discharge values as inputs.

scholarly journals Delayed improvement local search

2021 ◽  
Author(s):  
Heber F. Amaral ◽  
Sebastián Urrutia ◽  
Lars M. Hvattum
Keyword(s):  
Local Search ◽  
Heuristic Algorithms ◽  
Travelling Salesman Problem ◽  
Computation Time ◽  
The Novel ◽  
Local Optima ◽  
New Strategy ◽  
Max Cut Problem ◽  
Novel Method ◽  
Similar Solutions

AbstractLocal search is a fundamental tool in the development of heuristic algorithms. A neighborhood operator takes a current solution and returns a set of similar solutions, denoted as neighbors. In best improvement local search, the best of the neighboring solutions replaces the current solution in each iteration. On the other hand, in first improvement local search, the neighborhood is only explored until any improving solution is found, which then replaces the current solution. In this work we propose a new strategy for local search that attempts to avoid low-quality local optima by selecting in each iteration the improving neighbor that has the fewest possible attributes in common with local optima. To this end, it uses inequalities previously used as optimality cuts in the context of integer linear programming. The novel method, referred to as delayed improvement local search, is implemented and evaluated using the travelling salesman problem with the 2-opt neighborhood and the max-cut problem with the 1-flip neighborhood as test cases. Computational results show that the new strategy, while slower, obtains better local optima compared to the traditional local search strategies. The comparison is favourable to the new strategy in experiments with fixed computation time or with a fixed target.

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